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ME-Net: Towards Effective Adversarial Robustness with Matrix Estimation

ME-Net: Towards Effective Adversarial Robustness with Matrix Estimation

28 May 2019
Yuzhe Yang
Guo Zhang
Dina Katabi
Zhi Xu
    AAML
ArXivPDFHTML

Papers citing "ME-Net: Towards Effective Adversarial Robustness with Matrix Estimation"

41 / 41 papers shown
Title
Diffusion-based Adversarial Purification from the Perspective of the Frequency Domain
Diffusion-based Adversarial Purification from the Perspective of the Frequency Domain
Gaozheng Pei
Ke Ma
Yingfei Sun
Qianqian Xu
Qingming Huang
DiffM
45
0
0
02 May 2025
Robust Overfitting Does Matter: Test-Time Adversarial Purification With
  FGSM
Robust Overfitting Does Matter: Test-Time Adversarial Purification With FGSM
Linyu Tang
Lei Zhang
AAML
35
3
0
18 Mar 2024
Purify++: Improving Diffusion-Purification with Advanced Diffusion
  Models and Control of Randomness
Purify++: Improving Diffusion-Purification with Advanced Diffusion Models and Control of Randomness
Boya Zhang
Weijian Luo
Zhihua Zhang
34
10
0
28 Oct 2023
Enhancing Adversarial Robustness via Score-Based Optimization
Enhancing Adversarial Robustness via Score-Based Optimization
Boya Zhang
Weijian Luo
Zhihua Zhang
DiffM
32
13
0
10 Jul 2023
Convolutional Visual Prompt for Robust Visual Perception
Convolutional Visual Prompt for Robust Visual Perception
Yun-Yun Tsai
Chengzhi Mao
Junfeng Yang
VLM
VPVLM
31
13
0
01 Mar 2023
Matrix Estimation for Individual Fairness
Matrix Estimation for Individual Fairness
Cindy Y. Zhang
Sarah H. Cen
Devavrat Shah
FaML
33
4
0
04 Feb 2023
On the Robustness of Randomized Ensembles to Adversarial Perturbations
On the Robustness of Randomized Ensembles to Adversarial Perturbations
Hassan Dbouk
Naresh R Shanbhag
AAML
23
7
0
02 Feb 2023
AdvDO: Realistic Adversarial Attacks for Trajectory Prediction
AdvDO: Realistic Adversarial Attacks for Trajectory Prediction
Yulong Cao
Chaowei Xiao
Anima Anandkumar
Danfei Xu
Marco Pavone
AAML
32
64
0
19 Sep 2022
Threat Model-Agnostic Adversarial Defense using Diffusion Models
Threat Model-Agnostic Adversarial Defense using Diffusion Models
Tsachi Blau
Roy Ganz
Bahjat Kawar
Alex M. Bronstein
Michael Elad
AAML
DiffM
27
26
0
17 Jul 2022
On the Limitations of Stochastic Pre-processing Defenses
On the Limitations of Stochastic Pre-processing Defenses
Yue Gao
Ilia Shumailov
Kassem Fawaz
Nicolas Papernot
AAML
SILM
39
30
0
19 Jun 2022
Exploring Adversarial Attacks and Defenses in Vision Transformers
  trained with DINO
Exploring Adversarial Attacks and Defenses in Vision Transformers trained with DINO
Javier Rando
Nasib Naimi
Thomas Baumann
Max Mathys
AAML
20
5
0
14 Jun 2022
Guided Diffusion Model for Adversarial Purification
Guided Diffusion Model for Adversarial Purification
Jinyi Wang
Zhaoyang Lyu
Dahua Lin
Bo Dai
Hongfei Fu
DiffM
196
82
0
30 May 2022
Diffusion Models for Adversarial Purification
Diffusion Models for Adversarial Purification
Weili Nie
Brandon Guo
Yujia Huang
Chaowei Xiao
Arash Vahdat
Anima Anandkumar
WIGM
218
419
0
16 May 2022
A Survey of Robust Adversarial Training in Pattern Recognition:
  Fundamental, Theory, and Methodologies
A Survey of Robust Adversarial Training in Pattern Recognition: Fundamental, Theory, and Methodologies
Zhuang Qian
Kaizhu Huang
Qiufeng Wang
Xu-Yao Zhang
OOD
AAML
ObjD
49
72
0
26 Mar 2022
Evaluating the Adversarial Robustness of Adaptive Test-time Defenses
Evaluating the Adversarial Robustness of Adaptive Test-time Defenses
Francesco Croce
Sven Gowal
T. Brunner
Evan Shelhamer
Matthias Hein
A. Cemgil
TTA
AAML
181
67
0
28 Feb 2022
Indiscriminate Poisoning Attacks on Unsupervised Contrastive Learning
Indiscriminate Poisoning Attacks on Unsupervised Contrastive Learning
Hao He
Kaiwen Zha
Dina Katabi
AAML
34
32
0
22 Feb 2022
CausalSim: A Causal Framework for Unbiased Trace-Driven Simulation
CausalSim: A Causal Framework for Unbiased Trace-Driven Simulation
Abdullah Alomar
Pouya Hamadanian
Arash Nasr-Esfahany
Anish Agarwal
MohammadIman Alizadeh
Devavrat Shah
CML
29
22
0
05 Jan 2022
Targeted Supervised Contrastive Learning for Long-Tailed Recognition
Targeted Supervised Contrastive Learning for Long-Tailed Recognition
Tianhong Li
Peng Cao
Yuan. Yuan
Lijie Fan
Yuzhe Yang
Rogerio Feris
Piotr Indyk
Dina Katabi
43
175
0
27 Nov 2021
Improving Robustness using Generated Data
Improving Robustness using Generated Data
Sven Gowal
Sylvestre-Alvise Rebuffi
Olivia Wiles
Florian Stimberg
D. A. Calian
Timothy A. Mann
36
293
0
18 Oct 2021
SEC4SR: A Security Analysis Platform for Speaker Recognition
SEC4SR: A Security Analysis Platform for Speaker Recognition
Guangke Chen
Zhe Zhao
Fu Song
Sen Chen
Lingling Fan
Yang Liu
AAML
25
12
0
04 Sep 2021
Regional Adversarial Training for Better Robust Generalization
Regional Adversarial Training for Better Robust Generalization
Chuanbiao Song
Yanbo Fan
Yichen Yang
Baoyuan Wu
Yiming Li
Zhifeng Li
Kun He
AAML
OOD
13
6
0
02 Sep 2021
Advances in adversarial attacks and defenses in computer vision: A
  survey
Advances in adversarial attacks and defenses in computer vision: A survey
Naveed Akhtar
Ajmal Mian
Navid Kardan
M. Shah
AAML
26
235
0
01 Aug 2021
Towards Robustness Against Natural Language Word Substitutions
Towards Robustness Against Natural Language Word Substitutions
Xinshuai Dong
A. Luu
Rongrong Ji
Hong Liu
SILM
AAML
35
113
0
28 Jul 2021
Adversarial purification with Score-based generative models
Adversarial purification with Score-based generative models
Jongmin Yoon
Sung Ju Hwang
Juho Lee
DiffM
25
151
0
11 Jun 2021
MagDR: Mask-guided Detection and Reconstruction for Defending Deepfakes
MagDR: Mask-guided Detection and Reconstruction for Defending Deepfakes
Zhikai Chen
Lingxi Xie
Shanmin Pang
Yong He
Bo Zhang
AAML
36
32
0
26 Mar 2021
On the human-recognizability phenomenon of adversarially trained deep
  image classifiers
On the human-recognizability phenomenon of adversarially trained deep image classifiers
Jonathan W. Helland
Nathan M. VanHoudnos
AAML
27
4
0
18 Dec 2020
RobustBench: a standardized adversarial robustness benchmark
RobustBench: a standardized adversarial robustness benchmark
Francesco Croce
Maksym Andriushchenko
Vikash Sehwag
Edoardo Debenedetti
Nicolas Flammarion
M. Chiang
Prateek Mittal
Matthias Hein
VLM
234
678
0
19 Oct 2020
Adversarial Machine Learning in Image Classification: A Survey Towards
  the Defender's Perspective
Adversarial Machine Learning in Image Classification: A Survey Towards the Defender's Perspective
G. R. Machado
Eugênio Silva
R. Goldschmidt
AAML
33
156
0
08 Sep 2020
Anti-Bandit Neural Architecture Search for Model Defense
Anti-Bandit Neural Architecture Search for Model Defense
Hanlin Chen
Baochang Zhang
Shenjun Xue
Xuan Gong
Hong Liu
Rongrong Ji
David Doermann
AAML
16
33
0
03 Aug 2020
Improving Calibration through the Relationship with Adversarial
  Robustness
Improving Calibration through the Relationship with Adversarial Robustness
Yao Qin
Xuezhi Wang
Alex Beutel
Ed H. Chi
AAML
40
25
0
29 Jun 2020
Rethinking the Value of Labels for Improving Class-Imbalanced Learning
Rethinking the Value of Labels for Improving Class-Imbalanced Learning
Yuzhe Yang
Zhi Xu
SSL
20
401
0
13 Jun 2020
Overfitting in adversarially robust deep learning
Overfitting in adversarially robust deep learning
Leslie Rice
Eric Wong
Zico Kolter
47
785
0
26 Feb 2020
On Adaptive Attacks to Adversarial Example Defenses
On Adaptive Attacks to Adversarial Example Defenses
Florian Tramèr
Nicholas Carlini
Wieland Brendel
A. Madry
AAML
104
820
0
19 Feb 2020
Deflecting Adversarial Attacks
Deflecting Adversarial Attacks
Yao Qin
Nicholas Frosst
Colin Raffel
G. Cottrell
Geoffrey E. Hinton
AAML
30
15
0
18 Feb 2020
Analysis of Random Perturbations for Robust Convolutional Neural
  Networks
Analysis of Random Perturbations for Robust Convolutional Neural Networks
Adam Dziedzic
S. Krishnan
OOD
AAML
24
1
0
08 Feb 2020
Fast is better than free: Revisiting adversarial training
Fast is better than free: Revisiting adversarial training
Eric Wong
Leslie Rice
J. Zico Kolter
AAML
OOD
99
1,158
0
12 Jan 2020
Defective Convolutional Networks
Defective Convolutional Networks
Tiange Luo
Tianle Cai
Mengxiao Zhang
Siyu Chen
Di He
Liwei Wang
AAML
27
3
0
19 Nov 2019
Adversarial Examples in Modern Machine Learning: A Review
Adversarial Examples in Modern Machine Learning: A Review
R. Wiyatno
Anqi Xu
Ousmane Amadou Dia
A. D. Berker
AAML
18
104
0
13 Nov 2019
Harnessing Structures for Value-Based Planning and Reinforcement
  Learning
Harnessing Structures for Value-Based Planning and Reinforcement Learning
Yuzhe Yang
Guo Zhang
Zhi Xu
Dina Katabi
OffRL
21
31
0
26 Sep 2019
On Robustness of Principal Component Regression
On Robustness of Principal Component Regression
Anish Agarwal
Devavrat Shah
Dennis Shen
Dogyoon Song
29
81
0
28 Feb 2019
Robust GANs against Dishonest Adversaries
Robust GANs against Dishonest Adversaries
Zhi Xu
Chengtao Li
Stefanie Jegelka
AAML
34
3
0
27 Feb 2018
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